The following commonly-assigned prior art references are considered to be the most pertinent to the present invention:
1. U.S. Pat. No. 4,945,538, granted Jul. 31, 1990, entitled "Method and Apparatus For Processing Sample Values in a Coded Signal Processing Channel." PA0 2. Allowed copending application U.S. Ser. No. 07/920,027, filed Jul. 27, 1992, now U.S. Pat. No. 5,282,216, granted Jan. 25, 1994, entitled "High Data Rate Decoding Method for Coded Signal Processing Channel." PA0 3. Allowed copending application U.S. Ser. No. 07/526,878, filed May 22, 1990, now U.S. Pat. No. 5,291,500, granted Mar. 1, 1994, entitled "Eight-Sample. Look-Ahead For Coded Signal Processing Channels." PA0 4. A. Patel, "A New Digital Signal Processing Channel For Data Storage Products," IEEE Trans. on Magnetics, Vol. 27, pp. 4579-4584, published November, 1991.
Each of the References 1-3 discloses a (1,7) ML decoder which uses a differing number of look-ahead digital sample values (y) derived from an analog read signal to execute several decisions for implementing a maximum likelihood (ML) decision. An ML decision involves comparing each of several linear functions (H) of the sample values (y) to the value of a threshold constant constituting a ML decision boundary related to that linear function. The linear functions and decision boundaries are chosen to minimize the overall mean square error in a ML sequence detection process using five, six, or eight look-ahead sample values of the read signal, as taught in References 1, 2, and 3, respectively.
Each Reference 1-3 discloses equations by which the decoder can compute nominal theoretical values of a set of boundary threshold constants from information about the shape of the analog pulse that is read back from the analog pulse transmitted over the (1,7) ML channel.
These references describe how to calculate and set at nominal theoretical values the test boundary threshold constants of look-ahead algorithms in order to accommodate variations in pulse shape when the pulse shapes are described in a simple form by six variables; i.e., when the read response to the positive and negative magnetic transitions are the pulses with the sample values . . . , 0, .alpha..sub.1, .beta..sub.1, .gamma..sub.1, 0, . . . and . . . , 0,-.alpha..sub.2, -.beta..sub.2, -.gamma..sub.2 0, . . . , respectively. They also state that the thresholds may be optimized empirically in response to the boundary crossings in actual test data, but do not disclose how.
Moreover, the boundary threshold constants, as computed by these equations, are generated from the read back pulse corresponding to a single transition. This assumes that the positive or negative readback pulse has a single form which can be described by three non-zero sample values. However, these computed thresholds may not be optimal because in reality signal processing channels are subject to nonlinearity, misequalization, and pulse asymmetry, in addition to pattern-dependent noise.
Reference 4 describes a five-sample look-ahead algorithm, including a geometrical interpretation of the decision algorithm. Boundary constants are determined from formulae related to the pulse shape response for a single magnetic transition, as in References 1-3.
None of these references discloses or suggests (i) determining nominal values of the threshold constants from a statistically significant number of readback pulse transitions that account for nonlinearity, misequalization, pulse asymmetry and pattern-dependent noise, and (ii) treating as potential errors in the detected data those which are too close to a selected threshold boundary, and automatically adjusting each threshold boundary so that a substantially equal number of error events occur at each side thereof.
There is a need for apparatus and methods for (i) determining for each particular magnetic recording device optimal value settings for the decision-boundary-constituting threshold constants for a (1,7) ML channel despite signal and noise anomalies in the readback pulse, (ii) establishing the decision boundary from a series of magnetic recording transitions instead of by artificially superpositioning the pulse shape corresponding to a single magnetic recording transition, and (iii) setting these boundary threshold constants at their optimal values by use of a predetermined sequence of recorded data or by use of any data with or without comparison to known data subject to signal and noise anomalies.